What are the hardware requirements for Bagel Hermes 34B Slerp?

Bagel Hermes 34B Slerp requires approximately 68.9 GB of VRAM and supports a context window of 195K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bagel Hermes 34B Slerp and how large is it?

Bagel Hermes 34B Slerp is developed by Weyaxi, a model with 34b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Bagel Hermes 34B Slerp perform on standard benchmarks?

Bagel Hermes 34B Slerp has the following published scores: MMLU 77.29. Compare against reference models on this page or on the LLM Explorer leaderboards.

Bagel Hermes 34B Slerp by Weyaxi — VRAM 68.9GB, 195K context

Name: Bagel Hermes 34B Slerp
Author: Weyaxi

Bagel Hermes 34B Slerp is an open-source language model by Weyaxi. Features: 34b LLM, VRAM: 68.9GB, Context: 195K, License: apache-2.0, Merged, LLM Explorer Score: 0.22, Arc: 70.7, HellaSwag: 85.7, MMLU: 77.3, GSM8K: 66.3.

Merged Model Conversational Endpoints compatible Llama Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Weyaxi/Bagel-Hermes-34B-Slerp

Bagel Hermes 34B Slerp Parameters and Internals

Model Type

text-generation

Additional Notes

This model was merged using the SLERP method combining Nous-Hermes-2-Yi-34B, bagel-dpo-34b-v0.2, and nontoxic-bagel-34b-v0.2 models.

LLM Name	Bagel Hermes 34B Slerp
Repository 🤗	https://huggingface.co/Weyaxi/Bagel-Hermes-34B-Slerp
Merged Model	Yes
Model Size	34b
Required VRAM	68.9 GB
Updated	2026-06-06
Maintainer	Weyaxi
Model Type	llama
Model Files	9.8 GB: 1-of-8 9.8 GB: 2-of-8 9.8 GB: 3-of-8 9.8 GB: 4-of-8 9.8 GB: 5-of-8 9.8 GB: 6-of-8 9.8 GB: 7-of-8 0.3 GB: 8-of-8
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	200000
Model Max Length	200000
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	64002
Torch Data Type	bfloat16

Rank the Bagel Hermes 34B Slerp capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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34B Beta	195K / 69.2 GB	8670	67
Smaug 34B V0.1	195K / 69.2 GB	8082	64
Casual Magnum 34B	195K / 68.8 GB	4	1
Yi 34B 200K	195K / 68.9 GB	9133	320
Bagel 34B V0.2	195K / 68.7 GB	259	41
Yi 34B 200K AEZAKMI V2	195K / 69.2 GB	57	12
Faro Yi 34B	195K / 69.2 GB	8208	6
Bagel DPO 34B V0.5	195K / 68.7 GB	8040	17
Smaug 34B V0.1 ExPO	195K / 69.2 GB	7812	0
Luminex 34B V0.1	195K / 68.9 GB	8566	8